A model for presenting accelerometer paradata in large studies: ISCOLE

Catrine E. Tudor- Locke; Emily F. Mire; Kara N. Dentro; Tiago V. Barreira; John M. Schuna; Pei Zhao; Mark S. Tremblay; Martyn Standage; Olga Sarmiento; Vincent Ochieng Onywera; Tim Olds; Victor Rodrigues Matsudo; José António Maia; Carol Ann Maher; Estelle Victoria Lambert; Anura Vishwanath Kurpad; Rebecca Kuriyan; Gang Hu; Mikael Fogelholm; Jean Philippe Chaput; Timothy S. Church; Peter T. Katzmarzyk; Stephanie T. Broyles; Ben P. Butitta; Catherine M. Champagne; Shannon H. Cocreham; Katy Drazba; Deirdre Deirdre M. Harrington; William D. Johnson; Dione Milauskas; Allison Tohme; Ruben Q. Rodarte; Bobby Amoroso; John Luopa; Rebecca H. Neiberg; Scott Rushing; Lucy Kate Lewis; Katia Ferrar; Effie Georgiadis; Rebecca Megan Stanley; Victor Keihan Matsudo; Sandra Mahecha Matsudo; Timóteo Leandro Araújo; Luís Carlos De Oliveira; Leandro Rezende; Luis Fabiano; Diogo Bezerra; Gerson Luis Ferrari; Priscilla Bélanger; Michael Marc Borghese; Charles Boyer; Allana G.W. LeBlanc; Claire E. Francis; Geneviève Leduc; Chengming Diao; Wei Li; Enquing qing Liu; Gongshu Liu; Hongyan Liu; Jian Ma; Yijuan Qiao; Huiguang Tian; Yue Wang; Tao Zhang; Fuxia Zhang; Olga Sarmiento; Julio Acosta; Yalta Alvira; María Paula Díaz; Rocio Gámez; Maria Paula Garcia; Luis Guillermo Gómez; Lisseth Heras González; Silvia Alejandra González; Carlos Grijalba; Leidys Gutiérrez; David Leal; Nicolás Lemus; Etelvina Mahecha; Maria Paula Mahecha; Rosalba Mahecha; Andrea Ramírez Varela; Paola Ríos; Andres Suarez; Camilo A. Triana; Elli Hovi; Jemina Kivelä; Sari M. Räsänen; Sanna Roito; Taru Saloheimo; Leena Valta; Deepa P. Lokesh; Michelle Stephanie D'Almeida; R. Annie Mattilda; Lygia F.M. Correa; D. Vijay; Lucy Joy Wachira; Stella Kagwiria Muthuri; Alessandra Da Silva Borges; Sofia Oliveira Sá Cachada; Raquel Nichele De Chaves; Thayse Natacha Gomes; Sara Isabel Pereira; Daniel Monteiro De Vilhena E Santos; Fernanda Karina Dos Santos; Pedro Gil Da Silva; Michele Caroline De Souza; Vicki E. Lambert; Matthew April; Monika Uys; Nirmala Naidoo; Nandi Synyanya; Madelaine T. Carstens; Sean P. Cumming; Clemens Drenowatz; Lydia G. Emm; Fiona Bridget Gillison; Julia Kirstey Zakrzewski; Ashley Braud; Sheletta G. Donatto; Corbin Lemon; Ana Jackson; Ashunti Pearson; Gina Pennington; Daniel Ragus; Ryan C. Roubion; John M. Schuna; Derek Wiltz; Alan Mark Batterham; Jacqueline Kerr; Michael W. Pratt; Angelo Pietrobelli

doi:10.1186/s12966-015-0213-5

A model for presenting accelerometer paradata in large studies: ISCOLE

Catrine E. Tudor- Locke, Emily F. Mire, Kara N. Dentro, Tiago V. Barreira, John M. Schuna, Pei Zhao, Mark S. Tremblay, Martyn Standage, Olga Sarmiento, Vincent Ochieng Onywera, Tim Olds, Victor Rodrigues Matsudo, José António Maia, Carol Ann Maher, Estelle Victoria Lambert, Anura Vishwanath Kurpad, Rebecca Kuriyan, Gang Hu, Mikael Fogelholm, Jean Philippe ChaputTimothy S. Church, Peter T. Katzmarzyk, Stephanie T. Broyles, Ben P. Butitta, Catherine M. Champagne, Shannon H. Cocreham, Katy Drazba, Deirdre Deirdre M. Harrington, William D. Johnson, Dione Milauskas, Allison Tohme, Ruben Q. Rodarte, Bobby Amoroso, John Luopa, Rebecca H. Neiberg, Scott Rushing, Lucy Kate Lewis, Katia Ferrar, Effie Georgiadis, Rebecca Megan Stanley, Victor Keihan Matsudo, Sandra Mahecha Matsudo, Timóteo Leandro Araújo, Luís Carlos De Oliveira, Leandro Rezende, Luis Fabiano, Diogo Bezerra, Gerson Luis Ferrari, Priscilla Bélanger, Michael Marc Borghese, Charles Boyer, Allana G.W. LeBlanc, Claire E. Francis, Geneviève Leduc, Chengming Diao, Wei Li, Enquing qing Liu, Gongshu Liu, Hongyan Liu, Jian Ma, Yijuan Qiao, Huiguang Tian, Yue Wang, Tao Zhang, Fuxia Zhang, Olga Sarmiento, Julio Acosta, Yalta Alvira, María Paula Díaz, Rocio Gámez, Maria Paula Garcia, Luis Guillermo Gómez, Lisseth Heras González, Silvia Alejandra González, Carlos Grijalba, Leidys Gutiérrez, David Leal, Nicolás Lemus, Etelvina Mahecha, Maria Paula Mahecha, Rosalba Mahecha, Andrea Ramírez Varela, Paola Ríos, Andres Suarez, Camilo A. Triana, Elli Hovi, Jemina Kivelä, Sari M. Räsänen, Sanna Roito, Taru Saloheimo, Leena Valta, Deepa P. Lokesh, Michelle Stephanie D'Almeida, R. Annie Mattilda, Lygia F.M. Correa, D. Vijay, Lucy Joy Wachira, Stella Kagwiria Muthuri, Alessandra Da Silva Borges, Sofia Oliveira Sá Cachada, Raquel Nichele De Chaves, Thayse Natacha Gomes, Sara Isabel Pereira, Daniel Monteiro De Vilhena E Santos, Fernanda Karina Dos Santos, Pedro Gil Da Silva, Michele Caroline De Souza, Vicki E. Lambert, Matthew April, Monika Uys, Nirmala Naidoo, Nandi Synyanya, Madelaine T. Carstens, Sean P. Cumming, Clemens Drenowatz, Lydia G. Emm, Fiona Bridget Gillison, Julia Kirstey Zakrzewski, Ashley Braud, Sheletta G. Donatto, Corbin Lemon, Ana Jackson, Ashunti Pearson, Gina Pennington, Daniel Ragus, Ryan C. Roubion, John M. Schuna, Derek Wiltz, Alan Mark Batterham, Jacqueline Kerr, Michael W. Pratt, Angelo Pietrobelli

Flinders University

Research output: Contribution to journal › Article › peer-review

13 Citations (Scopus)

Abstract

Background: We present a model for reporting accelerometer paradata (process-related data produced from survey administration) collected in the International Study of Childhood Obesity Lifestyle and the Environment (ISCOLE), a multi-national investigation of >7000 children (averaging 10.5 years of age) sampled from 12 different developed and developing countries and five continents. Methods: ISCOLE employed a 24-hr waist worn 7-day protocol using the ActiGraph GT3X+. Checklists, flow charts, and systematic data queries documented accelerometer paradata from enrollment to data collection and treatment. Paradata included counts of consented and eligible participants, accelerometers distributed for initial and additional monitoring (site specific decisions in the face of initial monitoring failure), inadequate data (e.g., lost/malfunction, insufficient wear time), and averages for waking wear time, valid days of data, participants with valid data (>4 valid days of data, including 1 weekend day), and minutes with implausibly high values (>20,000 activity counts/min). Results: Of 7806 consented participants, 7372 were deemed eligible to participate, 7314 accelerometers were distributed for initial monitoring and another 106 for additional monitoring. 414 accelerometer data files were inadequate (primarily due to insufficient wear time). Only 29 accelerometers were lost during the implementation of ISCOLE worldwide. The final locked data file consisted of 6553 participant files (90.0% relative to number of participants who completed monitoring) with valid waking wear time, averaging 6.5 valid days and 888.4 minutes/day (14.8 hours). We documented 4762 minutes with implausibly high activity count values from 695 unique participants (9.4% of eligible participants and <0.01% of all minutes). Conclusions: Detailed accelerometer paradata is useful for standardizing communication, facilitating study management, improving the representative qualities of surveys, tracking study endpoint attainment, comparing studies, and ultimately anticipating and controlling costs.

Original language	English
Article number	52
Journal	International Journal of Behavioral Nutrition and Physical Activity
Volume	12
Issue number	1
DOIs	https://doi.org/10.1186/s12966-015-0213-5
Publication status	Published - 20 Apr 2015

Keywords

Data collection
Evaluation studies
Exercise
Methods
Motor activity

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10.1186/s12966-015-0213-5

Cite this

Tudor- Locke, C. E., Mire, E. F., Dentro, K. N., Barreira, T. V., Schuna, J. M., Zhao, P., Tremblay, M. S., Standage, M., Sarmiento, O., Onywera, V. O., Olds, T., Matsudo, V. R., Maia, J. A., Maher, C. A., Lambert, E. V., Kurpad, A. V., Kuriyan, R., Hu, G., Fogelholm, M., ... Pietrobelli, A. (2015). A model for presenting accelerometer paradata in large studies: ISCOLE. International Journal of Behavioral Nutrition and Physical Activity, 12(1), [52]. https://doi.org/10.1186/s12966-015-0213-5

@article{eb649c5df2af436cb9ea22bf386f1594,

title = "A model for presenting accelerometer paradata in large studies: ISCOLE",

abstract = "Background: We present a model for reporting accelerometer paradata (process-related data produced from survey administration) collected in the International Study of Childhood Obesity Lifestyle and the Environment (ISCOLE), a multi-national investigation of >7000 children (averaging 10.5 years of age) sampled from 12 different developed and developing countries and five continents. Methods: ISCOLE employed a 24-hr waist worn 7-day protocol using the ActiGraph GT3X+. Checklists, flow charts, and systematic data queries documented accelerometer paradata from enrollment to data collection and treatment. Paradata included counts of consented and eligible participants, accelerometers distributed for initial and additional monitoring (site specific decisions in the face of initial monitoring failure), inadequate data (e.g., lost/malfunction, insufficient wear time), and averages for waking wear time, valid days of data, participants with valid data (>4 valid days of data, including 1 weekend day), and minutes with implausibly high values (>20,000 activity counts/min). Results: Of 7806 consented participants, 7372 were deemed eligible to participate, 7314 accelerometers were distributed for initial monitoring and another 106 for additional monitoring. 414 accelerometer data files were inadequate (primarily due to insufficient wear time). Only 29 accelerometers were lost during the implementation of ISCOLE worldwide. The final locked data file consisted of 6553 participant files (90.0% relative to number of participants who completed monitoring) with valid waking wear time, averaging 6.5 valid days and 888.4 minutes/day (14.8 hours). We documented 4762 minutes with implausibly high activity count values from 695 unique participants (9.4% of eligible participants and <0.01% of all minutes). Conclusions: Detailed accelerometer paradata is useful for standardizing communication, facilitating study management, improving the representative qualities of surveys, tracking study endpoint attainment, comparing studies, and ultimately anticipating and controlling costs.",

keywords = "Data collection, Evaluation studies, Exercise, Methods, Motor activity",

author = "{Tudor- Locke}, {Catrine E.} and Mire, {Emily F.} and Dentro, {Kara N.} and Barreira, {Tiago V.} and Schuna, {John M.} and Pei Zhao and Tremblay, {Mark S.} and Martyn Standage and Olga Sarmiento and Onywera, {Vincent Ochieng} and Tim Olds and Matsudo, {Victor Rodrigues} and Maia, {Jos{\'e} Ant{\'o}nio} and Maher, {Carol Ann} and Lambert, {Estelle Victoria} and Kurpad, {Anura Vishwanath} and Rebecca Kuriyan and Gang Hu and Mikael Fogelholm and Chaput, {Jean Philippe} and Church, {Timothy S.} and Katzmarzyk, {Peter T.} and Broyles, {Stephanie T.} and Butitta, {Ben P.} and Champagne, {Catherine M.} and Cocreham, {Shannon H.} and Katy Drazba and {Deirdre M. Harrington}, Deirdre and Johnson, {William D.} and Dione Milauskas and Allison Tohme and Rodarte, {Ruben Q.} and Bobby Amoroso and John Luopa and Neiberg, {Rebecca H.} and Scott Rushing and Lewis, {Lucy Kate} and Katia Ferrar and Effie Georgiadis and Stanley, {Rebecca Megan} and Matsudo, {Victor Keihan} and Matsudo, {Sandra Mahecha} and Ara{\'u}jo, {Tim{\'o}teo Leandro} and {De Oliveira}, {Lu{\'i}s Carlos} and Leandro Rezende and Luis Fabiano and Diogo Bezerra and Ferrari, {Gerson Luis} and Priscilla B{\'e}langer and Borghese, {Michael Marc} and Charles Boyer and LeBlanc, {Allana G.W.} and Francis, {Claire E.} and Genevi{\`e}ve Leduc and Chengming Diao and Wei Li and Liu, {Enquing qing} and Gongshu Liu and Hongyan Liu and Jian Ma and Yijuan Qiao and Huiguang Tian and Yue Wang and Tao Zhang and Fuxia Zhang and Olga Sarmiento and Julio Acosta and Yalta Alvira and D{\'i}az, {Mar{\'i}a Paula} and Rocio G{\'a}mez and Garcia, {Maria Paula} and G{\'o}mez, {Luis Guillermo} and Gonz{\'a}lez, {Lisseth Heras} and Gonz{\'a}lez, {Silvia Alejandra} and Carlos Grijalba and Leidys Guti{\'e}rrez and David Leal and Nicol{\'a}s Lemus and Etelvina Mahecha and Mahecha, {Maria Paula} and Rosalba Mahecha and {Ram{\'i}rez Varela}, Andrea and Paola R{\'i}os and Andres Suarez and Triana, {Camilo A.} and Elli Hovi and Jemina Kivel{\"a} and R{\"a}s{\"a}nen, {Sari M.} and Sanna Roito and Taru Saloheimo and Leena Valta and Lokesh, {Deepa P.} and D'Almeida, {Michelle Stephanie} and {Annie Mattilda}, R. and Correa, {Lygia F.M.} and D. Vijay and Wachira, {Lucy Joy} and Muthuri, {Stella Kagwiria} and {Da Silva Borges}, Alessandra and {S{\'a} Cachada}, {Sofia Oliveira} and {De Chaves}, {Raquel Nichele} and Gomes, {Thayse Natacha} and Pereira, {Sara Isabel} and {De Vilhena E Santos}, {Daniel Monteiro} and {Dos Santos}, {Fernanda Karina} and {Da Silva}, {Pedro Gil} and {De Souza}, {Michele Caroline} and Lambert, {Vicki E.} and Matthew April and Monika Uys and Nirmala Naidoo and Nandi Synyanya and Carstens, {Madelaine T.} and Cumming, {Sean P.} and Clemens Drenowatz and Emm, {Lydia G.} and Gillison, {Fiona Bridget} and Zakrzewski, {Julia Kirstey} and Ashley Braud and Donatto, {Sheletta G.} and Corbin Lemon and Ana Jackson and Ashunti Pearson and Gina Pennington and Daniel Ragus and Roubion, {Ryan C.} and Schuna, {John M.} and Derek Wiltz and Batterham, {Alan Mark} and Jacqueline Kerr and Pratt, {Michael W.} and Angelo Pietrobelli",

year = "2015",

month = apr,

day = "20",

doi = "10.1186/s12966-015-0213-5",

language = "English",

volume = "12",

journal = "International Journal of Behavioral Nutrition and Physical Activity",

issn = "1479-5868",

publisher = "BioMed Central Ltd.",

number = "1",

}

Tudor- Locke, CE, Mire, EF, Dentro, KN, Barreira, TV, Schuna, JM, Zhao, P, Tremblay, MS, Standage, M, Sarmiento, O, Onywera, VO, Olds, T, Matsudo, VR, Maia, JA, Maher, CA, Lambert, EV, Kurpad, AV, Kuriyan, R, Hu, G, Fogelholm, M, Chaput, JP, Church, TS, Katzmarzyk, PT, Broyles, ST, Butitta, BP, Champagne, CM, Cocreham, SH, Drazba, K, Deirdre M. Harrington, D, Johnson, WD, Milauskas, D, Tohme, A, Rodarte, RQ, Amoroso, B, Luopa, J, Neiberg, RH, Rushing, S, Lewis, LK, Ferrar, K, Georgiadis, E, Stanley, RM, Matsudo, VK, Matsudo, SM, Araújo, TL, De Oliveira, LC, Rezende, L, Fabiano, L, Bezerra, D, Ferrari, GL, Bélanger, P, Borghese, MM, Boyer, C, LeBlanc, AGW, Francis, CE, Leduc, G, Diao, C, Li, W, Liu, EQ, Liu, G, Liu, H, Ma, J, Qiao, Y, Tian, H, Wang, Y, Zhang, T, Zhang, F, Sarmiento, O, Acosta, J, Alvira, Y, Díaz, MP, Gámez, R, Garcia, MP, Gómez, LG, González, LH, González, SA, Grijalba, C, Gutiérrez, L, Leal, D, Lemus, N, Mahecha, E, Mahecha, MP, Mahecha, R, Ramírez Varela, A, Ríos, P, Suarez, A, Triana, CA, Hovi, E, Kivelä, J, Räsänen, SM, Roito, S, Saloheimo, T, Valta, L, Lokesh, DP, D'Almeida, MS, Annie Mattilda, R, Correa, LFM, Vijay, D, Wachira, LJ, Muthuri, SK, Da Silva Borges, A, Sá Cachada, SO, De Chaves, RN, Gomes, TN, Pereira, SI, De Vilhena E Santos, DM, Dos Santos, FK, Da Silva, PG, De Souza, MC, Lambert, VE, April, M, Uys, M, Naidoo, N, Synyanya, N, Carstens, MT, Cumming, SP, Drenowatz, C, Emm, LG, Gillison, FB, Zakrzewski, JK, Braud, A, Donatto, SG, Lemon, C, Jackson, A, Pearson, A, Pennington, G, Ragus, D, Roubion, RC, Schuna, JM, Wiltz, D, Batterham, AM, Kerr, J, Pratt, MW & Pietrobelli, A 2015, 'A model for presenting accelerometer paradata in large studies: ISCOLE', International Journal of Behavioral Nutrition and Physical Activity, vol. 12, no. 1, 52. https://doi.org/10.1186/s12966-015-0213-5

TY - JOUR

T1 - A model for presenting accelerometer paradata in large studies: ISCOLE

AU - Tudor- Locke, Catrine E.

AU - Mire, Emily F.

AU - Dentro, Kara N.

AU - Barreira, Tiago V.

AU - Schuna, John M.

AU - Zhao, Pei

AU - Tremblay, Mark S.

AU - Standage, Martyn

AU - Sarmiento, Olga

AU - Onywera, Vincent Ochieng

AU - Olds, Tim

AU - Matsudo, Victor Rodrigues

AU - Maia, José António

AU - Maher, Carol Ann

AU - Lambert, Estelle Victoria

AU - Kurpad, Anura Vishwanath

AU - Kuriyan, Rebecca

AU - Hu, Gang

AU - Fogelholm, Mikael

AU - Chaput, Jean Philippe

AU - Church, Timothy S.

AU - Katzmarzyk, Peter T.

AU - Broyles, Stephanie T.

AU - Butitta, Ben P.

AU - Champagne, Catherine M.

AU - Cocreham, Shannon H.

AU - Drazba, Katy

AU - Deirdre M. Harrington, Deirdre

AU - Johnson, William D.

AU - Milauskas, Dione

AU - Tohme, Allison

AU - Rodarte, Ruben Q.

AU - Amoroso, Bobby

AU - Luopa, John

AU - Neiberg, Rebecca H.

AU - Rushing, Scott

AU - Lewis, Lucy Kate

AU - Ferrar, Katia

AU - Georgiadis, Effie

AU - Stanley, Rebecca Megan

AU - Matsudo, Victor Keihan

AU - Matsudo, Sandra Mahecha

AU - Araújo, Timóteo Leandro

AU - De Oliveira, Luís Carlos

AU - Rezende, Leandro

AU - Fabiano, Luis

AU - Bezerra, Diogo

AU - Ferrari, Gerson Luis

AU - Bélanger, Priscilla

AU - Borghese, Michael Marc

AU - Boyer, Charles

AU - LeBlanc, Allana G.W.

AU - Francis, Claire E.

AU - Leduc, Geneviève

AU - Diao, Chengming

AU - Li, Wei

AU - Liu, Enquing qing

AU - Liu, Gongshu

AU - Liu, Hongyan

AU - Ma, Jian

AU - Qiao, Yijuan

AU - Tian, Huiguang

AU - Wang, Yue

AU - Zhang, Tao

AU - Zhang, Fuxia

AU - Sarmiento, Olga

AU - Acosta, Julio

AU - Alvira, Yalta

AU - Díaz, María Paula

AU - Gámez, Rocio

AU - Garcia, Maria Paula

AU - Gómez, Luis Guillermo

AU - González, Lisseth Heras

AU - González, Silvia Alejandra

AU - Grijalba, Carlos

AU - Gutiérrez, Leidys

AU - Leal, David

AU - Lemus, Nicolás

AU - Mahecha, Etelvina

AU - Mahecha, Maria Paula

AU - Mahecha, Rosalba

AU - Ramírez Varela, Andrea

AU - Ríos, Paola

AU - Suarez, Andres

AU - Triana, Camilo A.

AU - Hovi, Elli

AU - Kivelä, Jemina

AU - Räsänen, Sari M.

AU - Roito, Sanna

AU - Saloheimo, Taru

AU - Valta, Leena

AU - Lokesh, Deepa P.

AU - D'Almeida, Michelle Stephanie

AU - Annie Mattilda, R.

AU - Correa, Lygia F.M.

AU - Vijay, D.

AU - Wachira, Lucy Joy

AU - Muthuri, Stella Kagwiria

AU - Da Silva Borges, Alessandra

AU - Sá Cachada, Sofia Oliveira

AU - De Chaves, Raquel Nichele

AU - Gomes, Thayse Natacha

AU - Pereira, Sara Isabel

AU - De Vilhena E Santos, Daniel Monteiro

AU - Dos Santos, Fernanda Karina

AU - Da Silva, Pedro Gil

AU - De Souza, Michele Caroline

AU - Lambert, Vicki E.

AU - April, Matthew

AU - Uys, Monika

AU - Naidoo, Nirmala

AU - Synyanya, Nandi

AU - Carstens, Madelaine T.

AU - Cumming, Sean P.

AU - Drenowatz, Clemens

AU - Emm, Lydia G.

AU - Gillison, Fiona Bridget

AU - Zakrzewski, Julia Kirstey

AU - Braud, Ashley

AU - Donatto, Sheletta G.

AU - Lemon, Corbin

AU - Jackson, Ana

AU - Pearson, Ashunti

AU - Pennington, Gina

AU - Ragus, Daniel

AU - Roubion, Ryan C.

AU - Schuna, John M.

AU - Wiltz, Derek

AU - Batterham, Alan Mark

AU - Kerr, Jacqueline

AU - Pratt, Michael W.

AU - Pietrobelli, Angelo

PY - 2015/4/20

Y1 - 2015/4/20

N2 - Background: We present a model for reporting accelerometer paradata (process-related data produced from survey administration) collected in the International Study of Childhood Obesity Lifestyle and the Environment (ISCOLE), a multi-national investigation of >7000 children (averaging 10.5 years of age) sampled from 12 different developed and developing countries and five continents. Methods: ISCOLE employed a 24-hr waist worn 7-day protocol using the ActiGraph GT3X+. Checklists, flow charts, and systematic data queries documented accelerometer paradata from enrollment to data collection and treatment. Paradata included counts of consented and eligible participants, accelerometers distributed for initial and additional monitoring (site specific decisions in the face of initial monitoring failure), inadequate data (e.g., lost/malfunction, insufficient wear time), and averages for waking wear time, valid days of data, participants with valid data (>4 valid days of data, including 1 weekend day), and minutes with implausibly high values (>20,000 activity counts/min). Results: Of 7806 consented participants, 7372 were deemed eligible to participate, 7314 accelerometers were distributed for initial monitoring and another 106 for additional monitoring. 414 accelerometer data files were inadequate (primarily due to insufficient wear time). Only 29 accelerometers were lost during the implementation of ISCOLE worldwide. The final locked data file consisted of 6553 participant files (90.0% relative to number of participants who completed monitoring) with valid waking wear time, averaging 6.5 valid days and 888.4 minutes/day (14.8 hours). We documented 4762 minutes with implausibly high activity count values from 695 unique participants (9.4% of eligible participants and <0.01% of all minutes). Conclusions: Detailed accelerometer paradata is useful for standardizing communication, facilitating study management, improving the representative qualities of surveys, tracking study endpoint attainment, comparing studies, and ultimately anticipating and controlling costs.

AB - Background: We present a model for reporting accelerometer paradata (process-related data produced from survey administration) collected in the International Study of Childhood Obesity Lifestyle and the Environment (ISCOLE), a multi-national investigation of >7000 children (averaging 10.5 years of age) sampled from 12 different developed and developing countries and five continents. Methods: ISCOLE employed a 24-hr waist worn 7-day protocol using the ActiGraph GT3X+. Checklists, flow charts, and systematic data queries documented accelerometer paradata from enrollment to data collection and treatment. Paradata included counts of consented and eligible participants, accelerometers distributed for initial and additional monitoring (site specific decisions in the face of initial monitoring failure), inadequate data (e.g., lost/malfunction, insufficient wear time), and averages for waking wear time, valid days of data, participants with valid data (>4 valid days of data, including 1 weekend day), and minutes with implausibly high values (>20,000 activity counts/min). Results: Of 7806 consented participants, 7372 were deemed eligible to participate, 7314 accelerometers were distributed for initial monitoring and another 106 for additional monitoring. 414 accelerometer data files were inadequate (primarily due to insufficient wear time). Only 29 accelerometers were lost during the implementation of ISCOLE worldwide. The final locked data file consisted of 6553 participant files (90.0% relative to number of participants who completed monitoring) with valid waking wear time, averaging 6.5 valid days and 888.4 minutes/day (14.8 hours). We documented 4762 minutes with implausibly high activity count values from 695 unique participants (9.4% of eligible participants and <0.01% of all minutes). Conclusions: Detailed accelerometer paradata is useful for standardizing communication, facilitating study management, improving the representative qualities of surveys, tracking study endpoint attainment, comparing studies, and ultimately anticipating and controlling costs.

KW - Data collection

KW - Evaluation studies

KW - Exercise

KW - Methods

KW - Motor activity

UR - http://www.scopus.com/inward/record.url?scp=84928523439&partnerID=8YFLogxK

U2 - 10.1186/s12966-015-0213-5

DO - 10.1186/s12966-015-0213-5

M3 - Article

SN - 1479-5868

VL - 12

JO - International Journal of Behavioral Nutrition and Physical Activity

JF - International Journal of Behavioral Nutrition and Physical Activity

IS - 1

M1 - 52

ER -

A model for presenting accelerometer paradata in large studies: ISCOLE

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